Physical Sciences and Mathematics Commons^™

On The Use Of Machine Learning For Causal Inference In Extreme Weather Events, Yuzhe Wang

Discovery Undergraduate Interdisciplinary Research Internship

Machine learning has become a helpful tool for analyzing data, and causal Inference is a powerful method in machine learning that can be used to determine the causal relationship in data. In atmospheric and climate science, this technology can also be applied to predicting extreme weather events. One of the causal inference models is Granger causality, which is used in this project. Granger causality is a statistical test for identifying whether one time series is helpful in forecasting the other time series. In granger causality, if a variable X granger-causes Y: it means that by using all information without …

Polarimetric Radar And Vhf Lightning Observations In A Significantly Tornadic Supercell, Jacob Bruss

The Journal of Purdue Undergraduate Research

No abstract provided.

Redefining Research In Nanotechnology Simulations: A New Approach To Data Caching And Analysis, Darin Tsai, Alan Zhang, Aloysius Rebeiro

The Journal of Purdue Undergraduate Research

No abstract provided.

Agricultural Aerosols: The Impact Of Farming Activity On Ice Nucleating Particles, Joseph Robinson

The Journal of Purdue Undergraduate Research

Farming activities cause particles such as soil dust and plant material to be emitted into the air. Some of these aerosols can become ice nucleating particles (INPs), serving as seeds for ice and mixed-phase clouds. While there have been ground-based studies of these particles in the western Great Plains and a single air-based study in Indiana, there is a distinct lack of ground-based studies in the Midwest. In Indiana, over two-thirds of the state is farmland, with over 75% of land in Tippecanoe County used for agriculture. Despite farming being such an essential part of life in Indiana, the connection …

Processing Of Plastic Film From Potato Starch: Effect Of Drying Methods, Kourtney Collier, Samantha Goins, Austin Chirgwin, Isabelle Stanfield

The Journal of Purdue Undergraduate Research

Starch-based plastics are biodegradable, compostable compounds made of starch and plasticizers from natural sources. Their fabrication involves the starch-plasticizer reaction at 70–100°C followed by cooling and drying. Th e most common drying method is air drying (natural convection), which is effective but slow. Th e objective of this work is to study the effect of fast drying (forced convection) on the quality of the plastic film. Th is work compares the effects of drying conditions and drying rate on warpage, shrinkage rate, and presence of bubbles. Five drying methods are studied: (1) natural convection with uncovered petri dish, (2) natural …

Supporting The Protect Initiative, Josh Lefton, Jackson Murray, Ahmed Thabet, Sriram Baireddy, Prakash Shukla, Mridul Gupta, Reagan Becker, Julie Ertle, Tony Doan, Aerin Yang

Purdue Journal of Service-Learning and International Engagement

Recently, medication dosage errors have received more political and media attention. Dosage errors are the most common medical errors, affecting about 1.5 million people annually.

Furthermore, U.S. poison-control centers reported more than 200,000 cases per year of medication errors. These cases result in medical costs of around $3.5 billion, and children under 6 years old constitute approximately 30% of these cases.

The PROTECT Initiative (Preventing Overdoses and Treatment Errors in Children Taskforce) was launched in 2008 as a collaborative effort between public health agencies and patient advocates to minimize dosage errors.

In alignment with the PROTECT Initiative effort, this project …

Optimizing Cybersecurity Budgets With Attacksimulation, Alexander Master, George Hamilton, J. Eric Dietz

Faculty Publications

Modern organizations need effective ways to assess cybersecurity risk. Successful cyber attacks can result in data breaches, which may inflict significant loss of money, time, and public trust. Small businesses and non-profit organizations have limited resources to invest in cybersecurity controls and often do not have the in-house expertise to assess their risk. Cyber threat actors also vary in sophistication, motivation, and effectiveness. This paper builds on the previous work of Lerums et al., who presented an AnyLogic model for simulating aspects of a cyber attack and the efficacy of controls in a generic enterprise network. This paper argues that …

The Impact Of Service Dogs On Objective And Perceived Sleep Quality For Veterans With Ptsd, Madhuri Vempati, Elise A. Miller, Sarah C. Leighton, Leanne O. Nieforth, Marguerite O’Haire

Discovery Undergraduate Interdisciplinary Research Internship

One in four post-9/11 veterans (Fulton et al., 2015) have been diagnosed with posttraumatic stress disorder (PTSD), facing sleep disruptions as one of their most common symptoms. Service dogs have become an increasingly popular complementary intervention and anecdotes suggest they may impact sleep for veterans with PTSD. There is a need for empirical investigation into these claims through measurement and analysis of sleep quality.

The purpose of this study was to longitudinally investigate the impact of service dogs on sleep quality through both objective and subjective measures.

Participants in the treatment group (n=92) received a service dog after baseline, while …

Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting, Jordan Deakin, Dietmar Heinke

MODVIS Workshop

No abstract provided.

A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli

MODVIS Workshop

Neurons in cortical area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture. However, a functional account of how V2 neurons build selectivity for complex natural image features from their inputs – V1 neurons locally tuned for orientation and spatial frequency – remains elusive.

We made single-unit recordings in area V2 in two fixating rhesus macaques. We presented stimuli composed of multiple superimposed grating patches that localize contrast energy in space, orientation, and scale. V2 activity is modeled via a two-layer linear-nonlinear network, optimized to use a sparse combination of V1-like outputs to account …

Hhl Algorithm On The Honeywell H1 Quantum Computer, Adrik B. Herbert, Eric A. F. Reinhardt

Discovery Undergraduate Interdisciplinary Research Internship

The quantum algorithm for linear systems of equations (HHL algorithm) provides an efficient tool for finding solutions to systems of functions with a large number of variables and low sensitivity to changes in inputs (i.e. low error rates). For complex problems, such as matrix inversion, HHL requires exponentially less computational time as compared with classical computation methods. HHL can be adapted to current quantum computing systems with limited numbers of qubits (quantum computation bits) but a high reusability rate such as the Honeywell H1 quantum computer. Some methods for improving HHL have been proposed through the combination of quantum and …

Crowd-Machine Partnership On Road Infrastructure Quality Recognition And Resilience, Eric J. Thompson

Discovery Undergraduate Interdisciplinary Research Internship

Public roads are a vital component of modern-day society, as they are necessary for the transportation of people and capital; consequently, it is important that they are regularly and effectively maintained. Unfortunately, this maintenance is difficult to manage due to the sheer area that roads span. It is an arduous task to locate every instance of road damage, as well as to determine the urgency that each bit of damage necessitates. Repairing road damage has high costs in labor, time, and money. To provide a more efficient way to monitor road conditions, we are designing a mobile application that collects …

Climate Justice In Engineering Education, Tyler J. Morgan, Donna Riley, Caroline M. Camfield

Discovery Undergraduate Interdisciplinary Research Internship

The goal of this research is to design a learning module for Purdue first-year engineering (FYE) students to learn climate fundamentals, and the role of engineers in responding to climate justice challenges. There is a lack of climate material within these classes currently, leading to a lack of climate conscious engineers in the future. The project entailed reviewing and synthesizing a wide variety of previous research on climate change education in engineering, including key learning objectives and their assessment. Because one of the key foci of the first-year engineering sequence relates to data analysis and management, we focused our work …

Promoting Ecosystem Services By Implementing Agroforestry, Martin L. Emerson

Ideas: Exhibit Catalog for the Honors College Visiting Scholars Series

A recent proposal to enhance the sustainability of agriculture is agroforestry, the practice of integrating trees into farmland. This technique can be analyzed through the ecosystem services model, which describes the interrelatedness of natural land, managed land, producers, and consumers. Agroforestry could shelter crops from the adverse weather conditions as well as provide habitat for wildlife. On the other hand, implementing agroforestry would also entail the drawback of a substantial upfront cost. Environmental scientists propose that efforts to reinforce ecosystem services could play a significant role in mitigating the effects of global environmental change on agriculture.

Streamlining Project Development Through Planning & Environmental Linkages, Karen Hadley, Brett Lackey

Purdue Road School

As transportation agencies continue to explore ways to be more efficient in the project development process, they are embracing integrated methodologies like planning and environmental linkages. This tool is practical, yet highly effective and inclusive, and teams across the country are experiencing its value. This presentation will highlight a variety of use cases, discuss lessons learned and best practices, and specifically address how planning and environmental linkages can be applied in Indiana and the Midwest.

A Decade Later – Us 31 Mitigation, Summer R. Elmore

Purdue Road School

Significant transportation projects are designed and built, but that’s not the end of the story. Wetland and stream mitigation efforts, including monitoring and maintenance, may continue for a decade. This presentation will showcase INDOT mitigation sites—from their creation a decade ago to the awesome results—for projects like US-31. We’ll share timelines, photos, quality data, and challenges identified and addressed over the years.

Comparison Of The Performance Of The Observation-Based Hybrid Edmf And Edmf-Tke Pbl Schemes In 2020 Tropical Cyclone Forecasts From The Globalnested Hurricane Analysis And Forecast System, Andrew Hazelton, Jun A. Zhang, Sundararaman Gopalakrishnan

Department of Earth, Atmospheric, and Planetary Sciences Faculty Publications

Better representation of the planetary boundary layer (PBL) in numerical models is one of the keys to improving forecasts of TC structure and intensity, including rapid intensification. To meet this goal, our recent work has used observations to improve the eddy-diffusivity mass flux with prognostic turbulent kinetic energy (EDMF-TKE) PBL scheme in the Hurricane Analysis and Forecast System (HAFS). This study builds on that work by comparing a modified version of EDMF-TKE (MEDMF-TKE) with the hybrid EDMF scheme based on a K-profile method (HEDMF-KP) in the 2020 HAFS-globalnest model. Verification statistics based on 101 cases in the 2020 season demonstrate …

Password Managers: Secure Passwords The Easy Way, Alexander Master

CERIAS Technical Reports

Poor passwords are often the central problem identified when data breaches, ransomware attacks, and identity fraud cases occur. This Purdue Extension publication provides everyday users of Internet websites and computer systems with tools and strategies to protect their online accounts. Securing information access with password managers can be convenient and often free of cost, on a variety of devices and platforms. “Do’s and Don’ts” of password practices are highlighted, as well as the benefits of multi-factor authentication. The content is especially applicable for small businesses or non-profits, where employees often share access to systems or accounts.

Sok: Analysis Of Software Supply Chain Security By Establishing Secure Design Properties, Chinenye Okafor, Taylor R. Schorlemmer, Santiao Torres-Arias, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

This paper systematizes knowledge about secure software supply chain patterns. It identifies four stages of a software supply chain attack and proposes three security properties crucial for a secured supply chain: transparency, validity, and separation. The paper describes current security approaches and maps them to the proposed security properties, including research ideas and case studies of supply chains in practice. It discusses the strengths and weaknesses of current approaches relative to known attacks and details the various security frameworks put out to ensure the security of the software supply chain. Finally, the paper highlights potential gaps in actor and operation-centered …

Reflecting On Recurring Failures In Iot Development, Dharun Anandayuvaraj, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

As IoT systems are given more responsibility and autonomy, they offer greater benefits, but also carry greater risks. We believe this trend invigorates an old challenge of software engineering: how to develop high-risk software-intensive systems safely and securely under market pressures? As a first step, we conducted a systematic analysis of recent IoT failures to identify engineering challenges. We collected and analyzed 22 news reports and studied the sources, impacts, and repair strategies of failures in IoT systems. We observed failure trends both within and across application domains. We also observed that failure themes have persisted over time. To alleviate …

Exploiting Input Sanitization For Regex Denial Of Service, Efe Barlas, Xin Du, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Web services use server-side input sanitization to guard against harmful input. Some web services publish their sanitization logic to make their client interface more usable, e.g., allowing clients to debug invalid requests locally. However, this usability practice poses a security risk. Specifically, services may share the regexes they use to sanitize input strings — and regex-based denial of service (ReDoS) is an emerging threat. Although prominent service outages caused by ReDoS have spurred interest in this topic, we know little about the degree to which live web services are vulnerable to ReDoS.

In this paper, we conduct the first black-box …

Discrepancies Among Pre-Trained Deep Neural Networks: A New Threat To Model Zoo Reliability, Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Training deep neural networks (DNNs) takes significant time and resources. A practice for expedited deployment is to use pre-trained deep neural networks (PTNNs), often from model zoos.collections of PTNNs; yet, the reliability of model zoos remains unexamined. In the absence of an industry standard for the implementation and performance of PTNNs, engineers cannot confidently incorporate them into production systems. As a first step, discovering potential discrepancies between PTNNs across model zoos would reveal a threat to model zoo reliability. Prior works indicated existing variances in deep learning systems in terms of accuracy. However, broader measures of reliability for PTNNs from …

An Empirical Study On The Impact Of Deep Parameters On Mobile App Energy Usage, Qiang Xu, James C. Davis, Y Charlie Hu, Abhilash Jindal

Department of Electrical and Computer Engineering Faculty Publications

Improving software performance through configuration parameter tuning is a common activity during software maintenance. Beyond traditional performance metrics like latency, mobile app developers are interested in reducing app energy usage. Some mobile apps have centralized locations for parameter tuning, similar to databases and operating systems, but it is common for mobile apps to have hundreds of parameters scattered around the source code. The correlation between these "deep" parameters and app energy usage is unclear. Researchers have studied the energy effects of deep parameters in specific modules, but we lack a systematic understanding of the energy impact of mobile deep parameters. …

Reflections On Software Failure Analysis, Paschal C. Amusuo, Aishwarya Sharma, Siddharth R. Rao, Abbey Vincent, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Failure studies are important in revealing the root causes, behaviors, and life cycle of defects in software systems. These studies either focus on understanding the characteristics of defects in specific classes of systems or the characteristics of a specific type of defect in the systems it manifests in. Failure studies have influenced various software engineering research directions, especially in the area of software evolution, defect detection, and program repair.

In this paper, we reflect on the conduct of failure studies in software engineering. We reviewed a sample of 52 failure study papers. We identified several recurring problems in these studies, …

Towards A Burden-Free Implicit Authentication For Wearable Device Users, Bryan Lee, Sudip Vhaduri

Discovery Undergraduate Interdisciplinary Research Internship

The state of current knowledge-based wearable authentication systems requires users to physically interact with a device to initiate and validate their presence, thereby imposing a burden on the user. However, with the recent advancements of sensor technologies in consumer smart wearables (e.g., Fitbit and Apple watches), we were able to utilize vectors of statistical features extracted from the continuous stream of data from these IoT devices to implicitly validate a user's activities and its spatiotemporal context via the use of machine learning techniques. To improve the performance of our models, additional soft biometric data (i.e., respiratory sounds) was collected, and …